Determinants of Foreign Direct Investment in Chinese Cities: Evidence from Liaoning Province
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China has become an urbanized country and the number of Chinese mega cities has been increasing, making Chinese urbanism a significant force in the world. The Chinese economy still lacks sufficient domestic investment, requiring FDI to play the role of domestic entrepreneur.This study examines ten years of data from the 14 cities of Liaoning Province to explore local Chinese data from Chinese cities that provide contrasting examples from cities with different policy and different economic emphasis in order to discover what determines FDI in Chinese cities.This study used time series data with a random effects GLS regression model to estimate the factors correlating with FDI.The dependent variable was FDI, measured in units of USD$10,000. Eleven independent variables were employed to test the effects on FDI of different factors identified in the literature review. These included population density, per capita GDP, tertiary industry, unemployment, real estate employment, ICT employment, science and technology employment, health and social welfare employment, personal income tax, government debt, and a dummy variable for the Coastal Economic Zone. All of the independent variables were significant except for the dummy variable.All of the significant variables were positive except for health and social welfare employment, which was negative. The findings were consistent with predictions, except for the positive result for real estate employment.
Abstract
China has become an urbanized country and the number of Chinese mega cities has been increasing, making Chinese urbanism a significant force in the world. The Chinese economy still lacks sufficient domestic investment, requiring FDI to play the role of domestic entrepreneur.This study examines ten years of data from the 14 cities of Liaoning Province to explore local Chinese data from Chinese cities that provide contrasting examples from cities with different policy and different economic emphasis in order to discover what determines FDI in Chinese cities.This study used time series data with a random effects GLS regression model to estimate the factors correlating with FDI.The dependent variable was FDI, measured in units of USD$10,000. Eleven independent variables were employed to test the effects on FDI of different factors identified in the literature review. These included population density, per capita GDP, tertiary industry, unemployment, real estate employment, ICT employment, science and technology employment, health and social welfare employment, personal income tax, government debt, and a dummy variable for the Coastal Economic Zone. All of the independent variables were significant except for the dummy variable.All of the significant variables were positive except for health and social welfare employment, which was negative. The findings were consistent with predictions, except for the positive result for real estate employment.
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